Musings on User Experience and Media Psychology

I am currently in the process of revising the draft of my ASMR project. Although I would love to have more data to draw more findings, I have ended the data collection process to focus on revisions. I have identified another theme or two that I didn’t originally include in my draft, but these largely support the conclusions I already made. I do think they will help explain the significance of my project a little more.

The feedback I received from the draft was invaluable. As I was writing, I found myself shifting focus from one idea to another too much, and the feedback is really helping me restructure the organization of my argument. The areas I am focusing on the most are the introduction and reframing my thesis to clearly communicate the purpose of this project and why it matters. I never made these points as explicit as I should have, and I realize this is very important for the structure of the rest of the paper (and for justifying the work I have done to this point). Also, I need to do a better job connecting my research questions to the literature and to the project’s purpose. They make sense in my head, but I know I didn’t communicate them on the page very well. I am also bringing in a bit more literature and incorporating better sign posting, especially in my lit review, to make a better synthesis of previous research and to aid in organization. Overall I am working on creating a more logical flow for the argument of the paper.

Peer reviewing another paper was also helpful in seeing how someone else approached the project. As I reviewed the other draft, I realized some areas where my draft was lacking. I had made notes of these that mirrored many of the notes I received as part of the feedback on my own paper. Writing these research papers is an iterative process, and I find myself clarifying my own thinking each time I revise. It also forces me to answer some of the harder questions that I had tried to avoid earlier in the research process. I plan to take the lessons learned from this to apply to subsequent research projects and to clarify the big issues like significance and project purpose more explicitly at the beginning of the research process, rather than trying to justify them retroactively. It’s not that I didn’t have a plan or concept of these, but I would have benefitted from actually writing the introduction prior to conducting the interviews and textual analysis. I think this would have helped keep the project more focused.

One key theme that has emerged is how users of ASMR videos identify with certain ASMRtists over others and follow them as fans. As I had previously indicated, there appears to be a para-social relationship at play. Individuals indicated being most attached to those who can elicit triggers in them more readily. This is a very personalized process and seems deeply bound in notions of intimacy and connection. In addition, many users indicated having a favorite video that they go back to time and time again, especially one they have identified as either being effective in giving them “the tingles” or for helping them fall asleep. For the latter, ASMR videos without visuals were the most commonly cited by members of the ASMR community because they allow the users to focus on the desired audio effect without distraction. Overall, this process of discovery, identification, and bonding is one that ASMR users take very seriously and consider an important part of the ASMR experience.

Despite the prevalence of role playing ASMR videos online, only a few users have indicated that role playing, costumes, and other visuals are an important part of the ASMR experience. These seem to be more important to ASMRtists who view their productions as performances and go to painstaking effort to infuse their ASMR videos with excessive detail and intentionality. Whether or not the visuals and immersive nature of role playing add to the triggers is still unclear.

Another theme is the discovery of their ability to experience ASMR and the connection to others who also enjoy the experience. Most members of the ASMR community have an extended history of experiencing this phenomenon but did not have a name to attribute to it or a framework to understand it until discovering the ASMR community. Finding a label helped them identify what they were experiencing and made them feel normalized by it. Many ASMR users feel special for having a heightened sensibility to the ASMR phenomenon; however, they are also very open to extending the experience to others. Forming a community that shares this experience is an important part of their identification with ASMR and provided users with a sense of belonging and acceptance. Several users indicated their hesitancy in discussing their use of ASMR videos with friends and family outside the ASMR community for fear of judgment or misunderstanding.

Although I entered the study of ASMR communities without a solid theoretical framework, I believe I have now found a fruitful explanation in Symbolic Convergence Theory (Bormann, 1985). Originally conceived as a social theory of small group communication, Symbolic Convergence Theory (SCT) can help explain group cohesion in digital communities (Bormann, 1985). Within SCT, fantasy theme analysis offers a means by which shared fantasies unite a group consciousness. I believe this offers a promising lens to view the ASMR community. I will need to draw on more literature of Symbolic Convergence Theory and how it explains the ways in which the ASMR community coheres.

Somewhat discouraged by the small amount of participants I have been able to recruit for interviews so far, I began to turn to the online ASMR forums to see if I could answer my research questions with the discussion threads that already exist. I had previously contacted and gained permission from the moderators of a few ASMR forums to study the online discussion for the purposes of this research, so that was inherently my implied backup plan. Although I intended this portion of the study to be supplemental to the more robust interview responses, I am happy to report that there is a rich discourse surrounding ASMR in digital spaces that gets to most, if not all, of my research questions. Sharing ASMR experiences with fellow ASMR enthusiasts online seems to be more conducive to uncovering authentic insights than responding to an outsider to the community who is “studying” them. As a result, I think the interviews I have collected are now the supplement to the textual analysis of these discussion forums. I am glad that I was able to complete at least some interviews because what I am finding online aligns with the responses I have received in my interviews. These findings are still coming into being, but I am starting to be able to get glimpses of some emerging themes.

One finding that is beginning to become evident is that users of ASMR videos turn to these videos primarily for pleasure and escape. This is consistent with the findings of Barratt and Davis (2015) in their online study of 475 users of ASMR videos. Across the online forums and the interviews many people cite stress relief, mood enhancement, stimulation (both sexual and non-sexual), and relaxation as key reasons for using ASMR videos. On a related note, many users also indicated using ASMR videos to help them fall asleep. Although this is antithetical to the stimulation use reported by some, it is consistent with the stress relief and relaxation uses cited by others.

The types of ASMR videos users indicated watching most frequently and enjoying the most differed as well, but this is likely the result of differences in the gratifications sought from using these videos. Many participants in the discussion threads also follow specific ASMR performers as fans and have formed para-social relationships with them. This is not surprising, given the intimate nature of many of these videos. A desire for intimacy and connection seems to be another underlying reason for ASMR usage.

Some of my research questions are addressed indirectly, especially the responses of others to their use of ASMR videos. Although there are not many discussions on the topic of offline relations, I have found a few users who have indicated that they do not share their interest in ASMR with family members for fear of judgement or lack of understanding. These individuals indicated they don’t believe there is anything “wrong” or “weird” about it, but they believe others would just not understand. Because only a few users have posted on the topic, I am not sure I can generalize these feelings to the larger ASMR community. As I continue culling through the online forums and trying to collect a few more interviews I hope to be able to make some more definitive claims about ASMR.

At this point in my research, I have a few interviews completed. Over half of the people I have contacted either opted not to participate or have not yet responded to my inquiry, so this concerns me a little about my response rates and how much data I will be able to collect in the given timeframe. I have sent interview questions to about 20 people so far who have agreed to participate, but only 3 have returned their completed responses. I asked those who are completing asynchronous e-mail interviews to return them to me by the end of next week, so I am hopeful that I will have many more responses by then and will still have time to ask follow up questions if necessary. I have also been encouraging my participants to share my contact information with other ASMR enthusiasts who might be willing to participate. This form of snowball sampling has not been as organic as some of my past experiences with online recruitment. Topics with a dedicated fandom seem easier to recruit. There does seem to be a kind of ASMR fandom, but it is different than other fan groups, and they are not as eager to discuss their habits with an outsider to the community. Perhaps the perceived transgressive reputation of ASMR has made them less willing to share their experiences. I am trying to use the connections I have made to garner more support for my research within the ASMR community.

Although it is too early to draw themes from my data, I am realizing responses to my interview questions vary by the reasons why users are drawn to ASMR videos, which seem to impact how they interact with them. From the three completed responses I have received so far, I have one user who uses them to fall asleep, one who is “mostly just curious” about them, and one who only watches the videos of a particular ASMR YouTuber in a seemingly parasocial relationship. With so much variance in my limited data, I am wondering if I will be able to find consistent themes that resonate through my interviews.

Another challenge (maybe surprise) I have encountered in my data collection is the content of the ASMR videos I have analyzed. The more I watch, I feel the further down the rabbit hole I go. I continuously encounter videos that get more overtly sexual than I care to venture into, so I inevitably hit a point where I stop analyzing certain videos for fear of how they might develop. Since this part of my data collection is largely descriptive, I don’t think I need to analyze too many more videos. The ones I will look at yet will be those referenced specifically by interviewees, so I can make broader connections to their responses. Overall, I think the data collection process is starting to pick up momentum, but I still have looming concerns over the limited number of participants I may be able to recruit in the next few weeks.

Since I do not yet have any interview data to transcribe or code, I decided to explore some digital tools to help with the coding and analysis of YouTube videos. I am looking at ASMR videos on YouTube for their content (both in terms of what types of ASMR triggers are being manipulated as well as what is being said within the videos) and for their comments to see how users respond to this content. To do this, I need to incorporate a few different tools. First, I want to scrape the comments to these videos. Although there are plenty of scripts for Python and r out there, I was looking for a way to do this without coding. I found a browser-based YouTube comment scraper that was very easy to use: http://ytcomments.klostermann.ca/ The project is open source, and the code is available on GitHub.

I simply had to paste the YouTube video URL into the browser line on the site and select what I wanted to extract. I could choose Comment ID, Username, Date, Timestamp, Comment Text, Likes, and Replies, or any combination of those items. The Usernames, Comment Text, and Replies were the attributes of most use to me, but I just scraped it all anyway. You can choose to download the extracted attributes as JSON or a CSV file. I downloaded it into a CSV file and opened it in Excel. It took me less than 30 seconds to retrieve over 1500 comments to an ASMR video I was analyzing (see screenshot below).

The Excel file needed a little cleaning up, and I noticed that comments and replies that included emojis did not translate properly and just included a lot of random characters. That is not a big deal to me, though, because they are not part of my analysis. When implementing this for other videos, I would be more selective of the attributes and only extract those I was going to analyze. This would save me the hassle of having to delete extraneous data from the CSV file.

The second part of my analysis is to examine the content of the videos themselves. ASMR videos have a few qualities that make this process a bit complicated. One problem is that they tend to be very long, especially ones created to lull users to sleep; these can run several hours in length. Scrubbing through the videos can give a quick visual on what tools are being used to trigger ASMR effects but it does not reveal what is being said. One easy way of transcribing video footage is using Google’s speech recognition while playing back the video in real time. However, this is not practical when videos are hours long. Furthermore, ASMR videos, especially those employing whispering techniques, are not accurately transcribed with speech recognition software (I tried). Looking for a way to get a searchable transcript of the words spoken within the videos, I found https://www.diycaptions.com/

This site allowed me to paste the URL of the YouTube video I wanted to analyze and retrieve a transcription of the audio contained within the video. From there, I could search it, code it, and add subcaptions. The one set back is that if the video does not have transcription or captions enabled, there is no data to retrieve. Only about half of the ASMR videos I have tried to transcribe so far with DIY Captions Editor have been successful. For the others, I get the following message: “Unable to retrieve automatic captions for this video. If the video has captions or subtitles, please notify the webmaster, Mike Ridgway, at diycaptions@gmail.com.” Nevertheless, it was very useful for the videos that had it enabled, and I was able to get a full transcript of an hour long video in about 10 seconds. As I move forward, I will likely use NVivo or a similar program to bring all these pieces together into one place to code these different parts and identify relationships between them. As much as I like analog coding and analysis, I know this project would be way too cumbersome without the use of these digital tools, and they will allow me to more accurately make connections between these disparate pieces to help draw meaning from the texts.

I tend to be a paper and highlighter kind of person, and I often do my coding of interviews and texts with these tangible techniques. I like to sort my data into piles, jot notes, and create binders. I even print out pages (and pages) of discussion threads and comments. That works sometimes. But if you look at my desk (or any other flat surface in my home for that matter), you’ll quickly see that it might not be working as well as I’d like to pretend. After a quick Google search for digital tools that can help aid me in my qualitative analysis workflow, I found a few contenders.

QDA Miner Lite is the free version of QDA Miner, which is a qualitative text analysis software designed “for the analysis of textual data such as interview and news transcripts, open-ended responses, etc. as well as for the analysis of still images” (“Free”, n.d.). Although the interface doesn’t seem to be anything special, the functionality is there. You can code texts, demarcate texts into segments and code them separately, make comments to the text or the segment, search for coded parts with Boolean terms, and render charts, graphs, and tag clouds from the frequency of codes. This is essentially the digital equivalent of what I would traditionally do on paper, so I find that attractive.

I also really like the interface of Delve, which does pretty much the same thing as QDA Miner, but it is a little more aesthetically pleasing. However, Delve is still under development. I haven’t tried to do too much with it yet, so I’m guessing I will hit a few bugs along the way.

As much as I tried to find a better tool than NVivo (just because I wanted to be different), there is a reason it is so popular. “NVivo is hands down the most powerful qualitative analysis tool there is on the market” (Spear, 2018, p. 1). NVivo can do everything that QDA Miner and Delve can do, plus a lot more. I especially like that you can work with video as an imported file. This is especially valuable for this research project because I am looking at ASMR videos on YouTube and their comments from ASMR community members. NVivo will allow me to code both in the same environment. I also like that it allows me to map out the relationships between participants and texts. I understand that it might take a little longer to learn all the intricacies of NVivo, but there are tutorials on Lynda.com that guide you through how to use it effectively.

All of these tools will help me organize my texts, code and comment, and make the output of data visualizations much more appealing than my paper and highlighter method. I am looking forward to exploring these tools more deeply and putting them to use in my research of ASMR.

As a relatively new phenomena, ASMR does not have an extensive body of literature from which to draw. I have identified a few studies that have explored the topic and offered some theoretical grounding for me to base my research questions. While some literature has looked at the aesthetic qualities of ASMR video production and the common characteristics of the content, others have examined the users of these videos.

Upon analysis of the content of ASMR videos and some interviews with users, Andersen (2015) determined that “ASMR videos create pleasure through a distant intimacy that relies on the heteronormative gender roles of care and the aural impression of the whisper” (p.685). However, the individual subjective user experience transcends this form of broad classification (Iossifidis, 2017). I am also interested in exploring how participation in online ASMR communities relates to users’ offline explorations of intimacy and understanding the role that ASMR plays in their personal interactions with others, and my research questions include:

1) How did they discover and/or become a part of the ASMR community?

2) How do they access the ASMR experience, using what platforms and what devices?

3) How do the affordances of the digital technologies used to create, distribute, and view these videos impact the subjective user experience?

4) How have others outside the ASMR community responded to their interests in ASMR?

5) How has the use of ASMR videos influenced their offline interpersonal relationships and offline explorations of intimacy?

So far I have begun examining the content of the ASMR videos hosted by the YouTube community, and I have been observing the discourse revolving around ASMR on reddit and Facebook. This has allowed me to identify some potential interviewees to begin my research. Now that we have obtained IRB approval, I will begin contacting these individuals this week to ask for their participation. I will be open to interviewing them through the means they are most comfortable, but I will likely be relying primarily on asynchronous e-mail exchanges.

Fredborg, Clark, and Smith (2017) created an ASMR checklist that asked respondents to rate each of 16 stimuli known to elicit an ASMR effect by the intensity of the effect it produces. These stimuli included whispering, tapping, haircut simulations and other common ASMR triggers. Although this study attempted to quantify the experience of ASMR users to determine if certain personality types were more prone to seek ASMR experiences (something that I am not interested in exploring), I am interested in using/adapting this checklist as a way to begin to access the ASMR user experience. I was able to obtain the ASMR checklist and their data through the online appendices of the study (https://doi.org/10.3389/fpsyg.2017.00247). Although this will be a useful initial entry into their use of ASMR videos and the experiences it evokes as an icebreaker, the interview will draw out the responses to the above research questions.

Digital research spans worlds that exist both online and offline. Some digital research focuses on how digital interaction impacts the “real world” of users (boyd, 2015), while other digital research focuses entirely on the online interaction with no interest in the offline component of their lives (Boellstorff, 2008). For my research, I am interested in a little of each, though I am primarily going to access this through online methods.

ASMR came into being online, and since I am interested in examining the online ASMR community, it makes the most sense to examine the community online because that is where it exists. There is also an advantage to only interacting online with participants because it grants them a certain level of distance and anonymity that may make them feel more comfortable sharing their views and opinions with me. Furthermore, because many users adopt a persona for their participation in the ASMR community, they are more likely to affiliate with that identity in an online setting. This is the identity I am most interested in accessing for my research.

However, ASMR communities do contribute to a blurring of public and private, creating an intimate atmosphere in a mediated environment. As a result, these communities establish a sense of place for this virtual interaction. Miller and Slater (2000) explain the ‘virtuality’ of internet-based media as media that “can provide both means of interaction and modes of representation that add up to ‘spaces’ or ‘places’ that participants can treat as if they were real” (p. 4).

Although there are some ASMR experiences that exist in the physical world, the online ASMR community is the object of inquiry for my research and is distinctly different than physical ASMR environments. I first became aware of ASMR through the Netflix series “Follow This” that traces BuzzFeed reporters as they investigate their stories. In the episode devoted to ASMR, reporter Scaachi Koul explored the online community as well as the physical places for ASMR, which included a Brooklyn-based ASMR spa called Whisperlodge. In her article, Koul (2018) explains the difference in the online versus offline ASMR experiences:

“The internet has changed how we live — I think almost entirely in memes at this point — so of course it would change how much or how little we’re willing to give in a social interaction. But Whisperlodge forces you to play along, which is exactly why it can’t really translate into a pleasurable IRL experience… Online, ASMR works because you can turn your brain off and not worry about any of that other stuff; Whisperlodge takes the tenets of online intimacy — while also dragging along with it all the unpleasant parts of human interaction, like eye contact and small talk — and lets people get oddly close to your face” (p. 1).

Although there may be insights to be gained from conducting in-person interviews, I feel that maintaining the atmosphere of the online community trumps any benefits of offline methods.

References

Boellstorff, T. (2008). Coming of Age in Second Life. Princeton, NJ: Princeton University Press.

Digital research often carries unique ethical considerations, so working with online communities requires careful deliberation about the ethical expectations for participation and observation within those communities. This is especially true for online communities that center around topics and themes typically located in the private sphere. ASMR is one such topic that conveys an implied intimacy and inherent privacy amongst its community members (Andersen, 2015).

Convery and Cox (2012) explain, “the perception of privacy very much depends on a group’s protocols and privacy boundaries” (p. 51). Because the ASMR community seeks to establish an intimate environment designed to elicit physiological and emotional responses amongst its participants, they have established privacy boundaries that separate it from a public forum. However, the protocols for navigating this space are not made explicit for those outside the community. Unsolicited observation may be perceived as invasive and voyeuristic.

Before beginning my analysis of these various ASMR communities, I will first contact the moderator of each to inform them of my research and to ask for permission to observe. Additionally, I will inquire about the protocols for making my presence known and for preserving privacy within these spaces.

I will have to initially observe the community, read existing posts, and watch posted ASMR videos before I can identify potential participants for interviews. However, I will only peruse these at a cursory level to achieve the minimal level of exposure required for initial inspection, after which I will obtain consent from participants before conducting a more detailed analysis of the community and its texts. Anyone who participates in an interview or who completes a qualitative questionnaire for this study will also provide informed consent before participating.

Participant anonymity is another extremely important ethical concern. Especially since the ASMR community is often misunderstood as overtly sexual and transgressive (Andersen, 2015), preserving anonymity protects participants from potential societal ramifications and stigma. In fact, one research question for this study addresses these perceptions of others toward the ASMR community and may reveal participants’ explicit desire to conceal their participation in ASMR communities. For these reasons, even if some participants wish to be identified, I will still preserve their anonymity by concealing their identity. “Given a conflict between participants’ wishes and what seems prudent for them, researchers sometimes need to err on the side of caution and anonymize participants against their wishes” (Bruckman, Luther, & Fiesler, 2015, p. 249). Since the potential harm is unknown, I will preserve participant anonymity and exclude any details which would allow them to be identified.

ASMR communities navigate an extremely private experience in a seemingly public forum. Understanding how these communities establish and preserve their own privacy boundaries will be essential to working within these communities; therefore, protecting this privacy and preserving anonymity will be my top ethical priorities for conducting this research study.

Autonomous Sensory Meridian Response (ASMR) is a sensory phenomenon where a tingling physiological sensation is triggered by auditory or visual stimuli. A growing online community of users has developed around ASMR to produce and share videos that are intended to evoke this sensation. Although ASMR enthusiasts first organized on Yahoo Groups (Andersen, 2015), YouTube has become the dominant platform for sharing ASMR video experiences (Iossifidis, 2017). Several other ASMR communities have since emerged on social sites such as reddit (www.reddit.com/r/asmr) and Facebook (https://www.facebook.com/theasmrcommunity/). These videos share many common attributes, including the use of whispering, tapping, and role playing as a means to trigger the ASMR effect (Smith, Fredborg, & Kornelsen, 2017).

This study aims to identify the underlying individual and group characteristics that allow these communities to cohere as well as to explore how the technological affordances of the platforms used to share ASMR videos facilitate these experiences. Online interviews and qualitative questionnaires will be used to explore the subjective experience of members of the ASMR community. Research questions to be explored include:

1) How did they discover and/or become a part of the ASMR community?

2) How do they access the ASMR experience, using what platforms and what devices?

3) How do the affordances of the digital technologies used to create, distribute, and view these videos impact the subjective user experience?

4) How have others outside the ASMR community responded to their interests in ASMR?

Participants will be recruited from the ASMR subreddit, the ASMR Community on Facebook, and the ASMR YouTube community (https://www.youtube.com/user/ASMRCommunity). After initial recruitment, snowball sampling will be used to identify additional participants.

As another means of accessing users’ subjective experiences, this study will also employ textual analysis of the ASMR videos posted within these communities and the user comments posted in response to those videos. Uses and gratifications of ASMR video production and reception will also be explored through textual analysis, online interviews, and qualitative questionnaires.